Records management capacity and compliance toolkits : a critical assessment.

This article seeks to present the results of a project that critically evaluated a series of toolkits for assessing records management capacity and/or compliance. These toolkits have been developed in different countries and sectors within the context of the e-environment and provide evidence of good corporate and information governance. Design/methodology/approach - A desk-based investigation of the tools was followed by an electronic Delphi with toolkit developers and performance measurement experts to develop a set of evaluation criteria. Different stakeholders then evaluated the toolkits against the criteria using cognitive walkthroughs and expert heuristic reviews. The results and the research process were reviewed via electronic discussion. Findings - Developed by recognised and highly respected organisations, three of the toolkits are software tools, whilst the fourth is a methodology. They are all underpinned by relevant national/international records management legislation, standards and good practice including, either implicitly or explicitly, ISO 15489. They all have strengths, complementing rather than competing with one another. They enable the involvement of other staff, thereby providing an opportunity for raising awareness of the importance of effective records management. Practical implications - These toolkits are potentially very powerful, flexible and of real value to organisations in managing their records. They can be used for a "quick and dirty" assessment of records management capacity or compliance as well as in-depth analysis. The most important criterion for selecting the appropriate one is to match the toolkit with the scenario. Originality/value - This paper aims to raise awareness of the range and nature of records management toolkits and their potential for varied use in practice to support more effective management of records

An Investigation into Mobile Based Approach for Healthcare Activities, Occupational Therapy System

This research is to design and optimize the high quality of mobile apps, especially for iOS. The objective of this research is to develop a mobile system for Occupational therapy specialists to access and retrieval information. The investigation identifies the key points of using mobile-D agile methodology in mobile application development. It considers current applications within a different platform. It achieves new apps (OTS) for the health care activities

Closing the loop: assisting archival appraisal and information retrieval in one sweep

In this article, we examine the similarities between the concept of appraisal, a process that takes place within the archives, and the concept of relevance judgement, a process fundamental to the evaluation of information retrieval systems. More specifically, we revisit selection criteria proposed as result of archival research, and work within the digital curation communities, and, compare them to relevance criteria as discussed within information retrieval's literature based discovery. We illustrate how closely these criteria relate to each other and discuss how understanding the relationships between the these disciplines could form a basis for proposing automated selection for archival processes and initiating multi-objective learning with respect to information retrieval

Principles in Patterns (PiP) : Project Evaluation Synthesis

Evaluation activity found the technology-supported approach to curriculum design and approval developed by PiP to demonstrate high levels of user acceptance, promote improvements to the quality of curriculum designs, render more transparent and efficient aspects of the curriculum approval and quality monitoring process, demonstrate process efficacy and resolve a number of chronic information management difficulties which pervaded the previous state. The creation of a central repository of curriculum designs as the basis for their management as "knowledge assets", thus facilitating re-use and sharing of designs and exposure of tacit curriculum design practice, was also found to be highly advantageous. However, further process improvements remain possible and evidence of system resistance was found in some stakeholder groups. Recommendations arising from the findings and conclusions include the need to improve data collection surrounding the curriculum approval process so that the process and human impact of C-CAP can be monitored and observed. Strategies for improving C-CAP acceptance among the "late majority", the need for C-CAP best practice guidance, and suggested protocols on the knowledge management of curriculum designs are proposed. Opportunities for further process improvements in institutional curriculum approval, including a re-engineering of post-faculty approval processes, are also recommended

Designing and evaluating the usability of a machine learning API for rapid prototyping music technology

To better support creative software developers and music technologists' needs, and to empower them as machine learning users and innovators, the usability of and developer experience with machine learning tools must be considered and better understood. We review background research on the design and evaluation of application programming interfaces (APIs), with a focus on the domain of machine learning for music technology software development. We present the design rationale for the RAPID-MIX API, an easy-to-use API for rapid prototyping with interactive machine learning, and a usability evaluation study with software developers of music technology. A cognitive dimensions questionnaire was designed and delivered to a group of 12 participants who used the RAPID-MIX API in their software projects, including people who developed systems for personal use and professionals developing software products for music and creative technology companies. The results from the questionnaire indicate that participants found the RAPID-MIX API a machine learning API which is easy to learn and use, fun, and good for rapid prototyping with interactive machine learning. Based on these findings, we present an analysis and characterization of the RAPID-MIX API based on the cognitive dimensions framework, and discuss its design trade-offs and usability issues. We use these insights and our design experience to provide design recommendations for ML APIs for rapid prototyping of music technology. We conclude with a summary of the main insights, a discussion of the merits and challenges of the application of the CDs framework to the evaluation of machine learning APIs, and directions to future work which our research deems valuable